Hannah Rae Kerner

Contact Information

Research

I am researching machine learning applications for planetary science.

My primary interest is in training models to recognize “novelty” or geologically interesting features in planetary data (images, spectra, etc.). The idea is to create artificially intelligent programs that can act like members of a science mission team to prioritize observations for review by human scientists to assist with tactical and strategic planning (e.g. deciding where to drive the rover and what surface features to investigate further), thus increasing the scientific return of exploration missions.

I also work on various machine learning tools that improve workflows for scientists and missions as well as doing the occasional neutron modeling.

I work on the following missions:

Lunar Polar Hydrogen Mapper (LunaH-Map): This 6U CubeSat mission was recently selected by NASA's Science Mission Directorate to fly as a secondary payload on first Exploration Mission (EM-1) of the Space Launch System (SLS), scheduled to launch in September 2018. The mission is led by Arizona State University (PI: Dr. Craig Hardgrove) and I'm the flight software lead. LunaH-Map is being designed to fly a pair of neutron spectrometers to map hydrogen abundances at the South Pole of the Moon.

Mars Science Laboratory (Curiosity): The research described in the above section is designed specifically for the Mastcam and Dynamic Albedo of Neutrons (DAN) science investigations onboard Curiosity.

Mars Exploration Rover (Opportunity): I am a downlink lead for the Pancam instrument onboard Opportunity.